title: " Nanostring_validation_report“

author: “Sridhar”

date: “8/22/2017”

output: html

Nanostring_validation

See email:
#NOTE CHANGE IN SAMPLE IDS BASED ON CARA’S EMAIL On Aug 9, 2017, at 5:37 PM, Shirai, Cara clunn@wustl.edu wrote:
Sid,
Yes, this is what I discussed with you Monday. The mouse # is correct and will dictate treatment.
The sude vs veh is switched.
Thanks, Cara
altough we changed the sample names as per the sample submission forms, mouse id allocated to veh in each cell type actually belonged to 5 hours sudemycin treated samples so we need change the read names after first name change based on file names.

Mouse ids 1,2,6 belong vehicle and mouse ids 8,9,11 belong to sudemycin treated cells at 5 hours

Column trasnfomation from file names to sample id ***

Load data for each cell type and change legend based on correct sample names

bul.both = read.csv("normalize_bulk_both.csv", sep = ',', header = T, stringsAsFactors = F)
bul.both = plyr::rename(bul.both, c(
  "X5hr.11.BULK.VEH.11" = "X5hr.11.BULK.SUDE.11",
  "X5hr.8.BULK.VEH.8" =     "X5hr.8.BULK.SUDE.8",
  "X5hr.9.BULK.VEH.9" = "X5hr.9.BULK.SUDE.9",
  "X5hr.2.BULK.SUDE.2" =    "X5hr.2.BULK.VEH.2",
  "X5hr.6.BULK.SUDE.6" =    "X5hr.6.BULK.VEH.6",
  "X5hr.1.BULK.SUDE.1" = "X5hr.1.BULK.VEH.1"))
dim(bul.both)

[1] 122 13

cellb.both = read.csv("normalize_bcell_both.csv", sep = ',', header = T, stringsAsFactors = F)
cellb.both = plyr::rename(cellb.both, c(
  "X5hr.8.B_CELL.VEH.8" =   "X5hr.8.B_CELL.SUDE.8",
  "X5hr.9.B_CELL.VEH.9" =   "X5hr.9.B_CELL.SUDE.9",
  "X5hr.11.B_CELL.VEH.11" = "X5hr.11.B_CELL.SUDE.11",
  "X5hr.6.B_CELL.SUDE.6" =  "X5hr.6.B_CELL.VEH.6",
  "X5hr.1.B_CELL.SUDE.1" =  "X5hr.1.B_CELL.VEH.1",
  "X5hr.2.B_CELL.SUDE.2" =  "X5hr.2.B_CELL.VEH.2"))
dim(cellb.both)

[1] 122 13

myec.both = read.csv("normalize_myeloid_both.csv", sep = ',', header = T, stringsAsFactors = F)
myec.both = plyr::rename(myec.both, c(
  "X5hr.8.MYE.VEH.8" =  "X5hr.8.MYE.SUDE.8",
  "X5hr.9.MYE.VEH.9" =  "X5hr.9.MYE.SUDE.9",
  "X5hr.11.MYE.VEH.11" =    "X5hr.11.MYE.SUDE.11",
  "X5hr.2.MYE.SUDE.2" = "X5hr.2.MYE.VEH.2",
  "X5hr.1.MYE.SUDE.1" = "X5hr.1.MYE.VEH.1",
  "X5hr.6.MYE.SUDE.6" = "X5hr.6.MYE.VEH.6"))
dim(myec.both)

[1] 122 13

Load previously validated probes n = 73 , Pull out values for validated probes from new data

valid.probes = read.table("validated_probes.txt", sep='\t', stringsAsFactors = F)
dim(valid.probes)

[1] 73 1

Bulk cells

####Number of valid probes bulk cells bulk cells have 73, 13 probes in common

dim(bul.valid.5all.z)

## [1] 49  7

dim(bul.valid.2all.z)

## [1] 49  7

dim(bul.valid.24all.z)

## [1] 48  7

Heatmap BULK

Hierarchical clustering BULK

BCELL

[1] 73 13 [1] 53 13

dim(cellb.valid.5all.z)

## [1] 39  7

dim(cellb.valid.2all.z)

## [1] 48  7

dim(cellb.valid.24all.z)

## [1] 37  7

Heatmap BCELL

Hierarchical Clustering BCELL

Myeloid Cells

[1] 73 13

dim(myec.valid.5all.z)

## [1] 39  7

dim(myec.valid.2all.z)

## [1] 43  7

dim(myec.valid.24all.z)

## [1] 37  7

Heatmap Myeloid Cells

Hierarchical Clustering Myeloid cells